Introduction

Pawel Delimata; Mikhail Ju Moshkov; Andrzej Skowron; Zbigniew Suraj

doi:10.1007/978-3-540-85638-2_1

Introduction

Pawel Delimata^*, Mikhail Ju Moshkov, Andrzej Skowron, Zbigniew Suraj

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The monograph is devoted to the study of inhibitory rules. In contrast to deterministic (standard) rules which have the relation attribute = value on the right-hand side, inhibitory rules have on the right-hand side the relation attibute ≠ value. For information systems [60, 63, 72], we consider inhibitory association rules which on the right-hand side can have an arbitrary attribute. For decision systems (decision tables) [60], we consider inhibitory decision rules containing on the right-hand side the decision attribute. It is worthwhile mentioning that in the rough set approach the decision rules are used for extension of approximations of concepts from given samples of objects on the whole universe of objects (see, e.g., [5, 6, 75]).

Original language	English (US)
Title of host publication	Inhibitory Rules in Data Analysis
Subtitle of host publication	A Rough Set Approach
Pages	1-8
Number of pages	8
Volume	163
DOIs	https://doi.org/10.1007/978-3-540-85638-2_1
State	Published - 2009
Externally published	Yes

Publication series

Name	Studies in Computational Intelligence
Volume	163
ISSN (Print)	1860-949X

ASJC Scopus subject areas

Artificial Intelligence

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10.1007/978-3-540-85638-2_1

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title = "Introduction",

abstract = "The monograph is devoted to the study of inhibitory rules. In contrast to deterministic (standard) rules which have the relation attribute = value on the right-hand side, inhibitory rules have on the right-hand side the relation attibute ≠ value. For information systems [60, 63, 72], we consider inhibitory association rules which on the right-hand side can have an arbitrary attribute. For decision systems (decision tables) [60], we consider inhibitory decision rules containing on the right-hand side the decision attribute. It is worthwhile mentioning that in the rough set approach the decision rules are used for extension of approximations of concepts from given samples of objects on the whole universe of objects (see, e.g., [5, 6, 75]).",

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AU - Delimata, Pawel

AU - Moshkov, Mikhail Ju

AU - Skowron, Andrzej

AU - Suraj, Zbigniew

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N2 - The monograph is devoted to the study of inhibitory rules. In contrast to deterministic (standard) rules which have the relation attribute = value on the right-hand side, inhibitory rules have on the right-hand side the relation attibute ≠ value. For information systems [60, 63, 72], we consider inhibitory association rules which on the right-hand side can have an arbitrary attribute. For decision systems (decision tables) [60], we consider inhibitory decision rules containing on the right-hand side the decision attribute. It is worthwhile mentioning that in the rough set approach the decision rules are used for extension of approximations of concepts from given samples of objects on the whole universe of objects (see, e.g., [5, 6, 75]).

AB - The monograph is devoted to the study of inhibitory rules. In contrast to deterministic (standard) rules which have the relation attribute = value on the right-hand side, inhibitory rules have on the right-hand side the relation attibute ≠ value. For information systems [60, 63, 72], we consider inhibitory association rules which on the right-hand side can have an arbitrary attribute. For decision systems (decision tables) [60], we consider inhibitory decision rules containing on the right-hand side the decision attribute. It is worthwhile mentioning that in the rough set approach the decision rules are used for extension of approximations of concepts from given samples of objects on the whole universe of objects (see, e.g., [5, 6, 75]).

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DO - 10.1007/978-3-540-85638-2_1

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BT - Inhibitory Rules in Data Analysis

ER -

Introduction

Abstract

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